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A study published in the International Journal of Communication Networks and Information Security (Vol. 16, No. 3, 2024) introduces a novel energy-conscious routing protocol for Mobile Ad hoc Networks (MANETs), the Power-Aware Intelligent Water Drops Routing Algorithm (PIWDRA).
Drawing inspiration from river systems and leveraging nature-inspired artificial intelligence, PIWDRA was designed to address a central challenge in mobile networking: how to conserve energy while maintaining reliable communication across dynamic, infrastructure-less environments.
At the heart of PIWDRA is the Intelligent Water Drops (IWD) metaheuristic, a physics-based algorithm originally modeled on how natural water drops find optimal paths by gradually displacing soil and creating channels of least resistance. In the digital equivalent, PIWDRA treats each data packet as a virtual water drop, capable of exploring a network of mobile nodes by probabilistically selecting paths that minimize energy usage, transmission delay, and hop count.
The algorithm begins by initializing the network, where nodes and their residual energy levels are detected and stored. Each link between nodes is assigned a cost based on a heuristic undesirability function, defined by the ratio of transmission delay to the energy level of the node, favoring links that offer high energy and low delay. A routing table is established to record paths as they are discovered.
From the source node, multiple intelligent drops are launched. Each drop chooses its next hop based on a probability rule inversely related to the link cost, making energy-rich, low-delay paths more attractive. The drops keep track of the nodes they visit to prevent loops and ensure efficient exploration.
When they reach the destination node, each complete path is evaluated using a composite metric that considers the total hop count, cumulative delay, and minimum energy level across the path. The path with the lowest combined cost is selected for data transmission.
Once a path is selected, the soil levels on each of its links are updated. In keeping with the IWD framework, more efficient paths have soil removed, while less desirable routes retain higher soil levels, discouraging future use.
This is coupled with velocity updates based on the drop’s travel time and energy consumption, which influence how much soil is modified on the route. The algorithm also performs a global update of soil levels to reinforce the best-performing paths across the network.
Unlike traditional IWD-based routing protocols, PIWDRA distinguishes itself by embedding power-awareness directly into its core decision-making process.
The routing logic does not merely account for energy passively but gives it the highest weight when evaluating network paths. This ensures that routes are selected not just for speed or distance, but for their ability to preserve the energy of nodes, thereby prolonging the operational life of the entire MANET.
To assess performance, the researchers implemented PIWDRA in the NS-3 simulation environment and compared it against four benchmark protocols: AODV, DSDV, IWDRA, and IWDHocNet.
They evaluated the system under varying pause times and numbers of active traffic sources to simulate changes in mobility and traffic load. In all scenarios, PIWDRA consistently delivered superior outcomes in packet delivery success, delay reduction, and energy efficiency.
The paper concludes with suggestions for future development, including the integration of congestion-aware routing mechanisms, intelligent traffic queue management, and the hybridization of PIWDRA with other AI models to enhance adaptability in increasingly complex mobile network environments.
By fusing natural system modeling with algorithmic intelligence, PIWDRA offers a robust, energy-efficient, and scalable routing solution for MANETs. Its design supports critical applications in remote healthcare delivery, disaster response, rural education, and any domain where infrastructure-free communication must be reliable and energy-aware. As mobile connectivity continues to expand into mission-critical areas, algorithms like PIWDRA provide a glimpse into how nature-inspired AI can reshape the way wireless networks operate.
About the Author
Dr. Augustina Dede Agor is a lecturer in the Department of Information Technology at the University of Professional Studies, Accra. She holds a PhD in Computer Science.
Her research focuses on metaheuristics, artificial intelligence, computer networks, security and energy-efficient communication in MANETs, neural networks, biometrics, and Automated Fingerprint Identification Systems (AFIS).
By Dr. Augustina Dede Agor
Lecturer, Department of Information Technology, University of Professional Studies, Accra
Contact: augustinadede.agor@upsamail.edu.gh
